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Dynamic Group Management to Improve the Scalability of PBFT
Jinsung Cho, Gwangyong Kim, Geunmo Kim, Bongjae Kim, Min Choi
http://doi.org/10.5626/JOK.2023.50.5.369
A consensus algorithm that affects the reliability and performance of a blockchain is used for identical decision-making of nodes participating in the consensus. PBFT(Practical Byzantine Falut Tolerance) is a voting-based consensus algorithm with an O(n2) time complexity. The scalability of PBFT is generally poor. This paper proposes a scheme for grouping the nodes participating in a PBFT-based blockchain network and dynamically managing each group by layering it. In addition, we create a mathematical model for estimating the expected time required for consensus of the proposed scheme. Afterwards, we propose a dynamic consensus algorithm for dynamically adjusting the structures of groups and layers based on the model for estimating the expected time of a consensus. As a result of the experiment, the proposed scheme improves the performance of the consensus time by about 97% on average compared to the group-based PBFT without hierarchical structures.
An Offloading Scheme for Reliable Data Processing of Swarm-drones
Hong Min, Bongjae Kim, Junyoung Heo, Jinman Jung
http://doi.org/10.5626/JOK.2018.45.10.990
With the developing drone-related technologies, autonomous drones have many applications. The offloading technique is used to execute high computational tasks that are stored in the cloud to preserve the limited resources of a drone. In this paper, we determine the effect of offloading by using cost analysis for swarm-drones considering task completion time and energy consumption. If the drones take more time and spend more energy while offloading their tasks to the cloud, drones divide a large task into small tasks. These tasks are run by using the drone’s own resources to process data reliably and efficiently. Our simulation results also show how the task completion time and the energy consumption infuence the offloading decision.
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